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Screening for key genes associated with invasive ductal carcinoma of the breast via microarray data analysis

机译:通过微阵列数据分析筛选与乳腺浸润性导管癌相关的关键基因

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The aim of this study was to identify key genes related to invasive ductal carcinoma (IDC) of the breast by analyzing gene expression data with bioinformatic tools. Microarray data set GSE31138 was downloaded from Gene Expression Omnibus, including 3 breast cancer tissue samples and 3 normal controls. Differentially expressed genes (DEGs) between breast cancer and normal control were screened out (FDR 2). Coexpression between genes was examined with String, and a network was then constructed. Relevant pathways and diseases were retrieved with KOBAS. A total of 56 DEGs were obtained in the IDC of the breast compared with normal controls. A gene coexpression network including 27 pairs of genes was constructed and all the genes in the network were upregulated. Further study indicated that most of the genes in the coexpression network were enriched in ECM-receptor interaction (COL4A2, FN1, and HMMR) and nucleotide excision repair (CETN2 and PCNA) pathways, and that the most significantly related disease was autoimmune lymphoproliferative syndromes. A number of DEGs were acquired through comparative analysis of gene expression data. These findings are beneficial in promoting the understanding of the molecular mechanisms in breast cancer. More importantly, some key genes were revealed via gene coexpression network analysis, which could be potential biomarkers for IDC of the breast.
机译:这项研究的目的是通过使用生物信息学工具分析基因表达数据来鉴定与乳腺浸润性导管癌(IDC)相关的关键基因。从Gene Expression Omnibus下载了微阵列数据集GSE31138,包括3个乳腺癌组织样品和3个正常对照。筛选出乳腺癌和正常对照之间的差异表达基因(DEG)(FDR 2)。用String检查基因之间的共表达,然后构建网络。使用KOBAS检索了相关的途径和疾病。与正常对照相比,在乳房的IDC中总共获得了56个DEG。构建了一个包含27对基因的基因共表达网络,网络中的所有基因均被上调。进一步的研究表明,共表达网络中的大多数基因都富含ECM-受体相互作用(COL4A2,FN1和HMMR)和核苷酸切除修复(CETN2和PCNA)途径,而最相关的疾病是自身免疫性淋巴组织增生综合征。通过基因表达数据的比较分析获得了许多DEG。这些发现有助于促进对乳腺癌分子机制的理解。更重要的是,通过基因共表达网络分析揭示了一些关键基因,这可能是乳房IDC的潜在生物标记。

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